Decentralized finance (DeFi) is thriving with stablecoins earning Treasury yields, while smaller players in the artificial intelligence (AI) industry face challenges in securing funding for the expansion of data centers with new GPUs.
A new stablecoin protocol called USD.AI aims to bridge that gap by converting idle liquidity in crypto into loans for the machines that train and operate artificial intelligence.
The protocol currently has around $345 million in circulation, and backs its synthetic dollar with short-term credit linked to NVIDIA GPUs located in data centers rented out to AI developers.
These GPUs generate revenue by selling compute time for model training and inference, with the cash flow used to service the debt that funds them. Lenders earn yield from these repayments instead of from token emissions, while borrowers gain access to specialized financing that often exceeds the risk appetite of most retail lenders.
USD.AI’s structure is built on three interconnected mechanisms designed to facilitate real-world credit on the blockchain.
The first, CALIBER, serves as the legal and technical bridge between a physical GPU and its on-chain representation. Each GPU financed through the protocol is stored in an insured data center and documented under U.S. commercial law, then tokenized as a non-fungible token (NFT) representing a legally enforceable claim to that hardware.
Loans are issued against these tokenized receipts, enabling capital raised on-chain to fund off-chain equipment with actual collateral. The next layer, the FiLo Curator, manages underwriting.
Curators originate and manage GPU loans while also providing their own first-loss capital, meaning they absorb any initial defaults before lenders are impacted. This structure decentralizes credit origination but keeps incentives aligned: Curators profit only when their borrowers succeed.
The final component, QEV, which stands for queue extractable value, manages liquidity. Instead of offering instant withdrawals, the system queues redemption requests, turning time into a market.
Users who wait are gradually repaid from monthly borrower repayments, while those needing quicker exits can pay a premium to move ahead in the line. That premium compensates patient lenders and maintains the solvency of the loan book.
The current yield for staked sUSDai fluctuates between 13% and 17%, supported by repayments from GPU operators rather than emissions or leverage loops.
USD.AI’s backers describe it as a prototype for a broader “InfraFi” model, decentralized infrastructure finance, that could eventually extend to renewable energy projects or decentralized computing networks.
For now, its success depends on a more immediate question: whether the economics of GPU leasing—a proxy for AI demand—can remain robust enough to ensure those repayments continue.
If they do, USD.AI could emerge as DeFi’s first large-scale bridge between on-chain capital and the real-world machinery behind artificial intelligence.
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